A curated list of Polars docs, talks, tools, examples & articles the internet has to offer.
Polars is a lightning-fast DataFrame library for Rust, Python, Node.js and R.
Implemented in Rust, Polars uses Apache Arrow Columnar Format as the memory model.
Just follow the guidelines by either:
- Filling a suggestion issue (easier).
- Opening a pull request.
- Documentation - Official user guide for Python, Rust and R.
- Documentation for Python API - Official API Reference for Python.
- Documentation for Rust API - Official API Reference for Rust.
- Documentation for Node.js API - Official API Reference for Node.js.
- Documentation for R API - Official API Reference for R (WIP).
- Github: Polars Github Organization - Official Polars Github repository.
- Blog posts from Polars - Official blogs posts from Polars.
- Modern Polars - A side by side comparison between Polars and Pandas containing code in both frameworks by (@kevinheavey).
- Using the Polars DataFrame Library - A blog post by Wei-Meng Lee to discover the basics of Polars and how it can be used in place of Pandas.
- Why Polars uses less memory than Pandas - A blog post by Itamar Turner-Trauring detailing some techniques to opptimize Pandas memory usage and see how Polars can provide an answer in some cases.
- Plodding with Polars in Python - A blog post by @amitrathore that introduces some basic features of Polars.
- Polars-lazy - A blog post by (@ritchie46) and @jorgecarleitao that introduces Polars' lazy API in Rust.
- Series of posts on Polars - A series of blogpost on Polars usage with a lot of useful tricks and information by (@braaannigan). Moreover, Liam also has a Data Analysis with Polars course on Udemy.
- Youtube videos about Polars - A series of short youtube videos about Polars by (@braaannigan)
- Alternatives to Pandas: Python Polars - An article that explores the Python Polars module as an alternative to Pandas, comparing their similarities and differences and providing some examples by (@JohnLockwood)
- Pandas vs Polars - A comparison on File I/O - A blog post that evaluates Polars and Pandas in terms of I/O performance and speed when handling large datasets by Wes Poulsen.
- Polars: Blazingly Fast DataFrames in Rust and Python - Introduction to Polars by databricks.
- Polars: The Next Big Python Data Science Library... written in Rust? - A short video tutorial to get started coding with Polars by @RobMulla.
- The Last Polars Dataframe vs. Pandas Dataframe Video You Should Ever See - A video that compares Polars and Pandas data frames.
- The Best library for building Data Pipelines... - A video that compares Pandas, Spark and Polars for working with data in Python by @RobMulla.
- polars for Python - Python
polars
package to use polars DataFrame from Python. - tidypolars
tidypolars
python library built on top of polars library that gives access to methods and functions familiar to R tidyverse users.
- polars for Rust - Rust
polars
crate to use polars DataFrame with Rust. - GeoPolars
Geopolars
Rust crate that extends the Polars DataFrame library for use with geospatial data.
- rpolars for R - R
rpolars
package to use polars DataFrame from R.
- nodejs-polars for Node.js - Node.js
rpolars
package to use polars DataFrame from Node.js.
- pola-rs (@pola-rs) - Github organisation for Polars (Twitter: @DataPolars).
- Ritchie Vink (@ritchie46) - Author of Polars
- Stijn de Gooijer (@stinodego) - Member of Polars organisation
- Danny van Kooten (@dannyvankooten) - Member of Polars organisation
- Søren Havelund Welling (@sorhawell) - Member of Polars organisation
- Alexander Beedie (@alexander-beedie) - Contributor to Polars projects
- Marco Edward Gorelli (@MarcoGorelli ) - Contributor to Polars projects
- Damien Dotta (@ddotta) - Maintainer of Awesome Polars list
Thanks goes to these contributors!